Lead reviews of machine learning, AI, and Generative AI models across TD to identify potential fairness and bias risks.
Represent Compliance in major projects, initiatives, and enterprise engagements.
Perform quantitative analyses to identify fair lending risks associated with model development and use.
Identify and recommend alternative approaches to mitigate fair lending bias arising from models.
Develop specialized analytical tools to support project-specific needs or ongoing review activities.
Compile, analyze, and generate ad-hoc analytical reports for internal stakeholders.
Lead research efforts by applying advanced statistical analysis and modeling expertise.
Provide advisory support to line-of-business model owners on compliance best practices aligned with internal policies and industry standards.
Independently manage end-to-end functional programs and deliverables.

Undergraduate degree required, advanced technical degree preferred (e.g., math, physics, engineering, finance or computer science)
1+ years relevant experience (includes postgraduate experience)
Master's degree in computer science, machine learning, AI, engineering, statistics, data science, mathematics or related field with 4+ years of relevant work experience
In-depth knowledge of AI/ML methodologies, concepts and theory including Generative AI, Deep Learning, modern Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG), Transformers, Diffusion models etc.
Experience with Deep Learning and Generative AI technology stacks and libraries such as PyTorch, PromptFlow, LangChain, HuggingFace, etc.
Proficient in one or more scripting/programming languages such as Python
Familiarity with cloud platforms (e.g., Azure, AWS) and big data technologies (e.g., PySpark, Hadoop)

Applied Machine Learning Scientist II

Key skills